# ESMValTool
# recipe_hyint_extreme_events.yml
---
documentation:
  title: Extreme events and HyInt diagnostics

  description: |
    Recipe calling the extreme_events diagnostic followed by the hyint diagnostic

  authors:
    - arnone_enrico
    - vonhardenberg_jost
    - broetz_bjoern
    - sandstad_marit
    - mohr_christianwilhelm

  maintainer:
    - arnone_enrico

  references:
    - giorgi11jc
    - giorgi14jgr
    - zhang11wcc

  projects:
    - c3s-magic

datasets:
  - {dataset: ACCESS1-0, project: CMIP5, exp: historical,  ensemble: r1i1p1, start_year: 1980, end_year: 1985}
  - {dataset: MPI-ESM-MR, project: CMIP5, exp: historical,  ensemble: r1i1p1, start_year: 1980, end_year: 1985}

preprocessors:
  preproc:
    mask_landsea:
      mask_out: sea

diagnostics:
  hyint_etccdi:
    description: Extreme events followed by HyInt hydroclimatic indices calculation and plotting
    variables:
      pr:
        preprocessor: preproc
        reference_dataset: "ACCESS1-0"
        mip: day
      tasmax:
        preprocessor: preproc
        reference_dataset: "ACCESS1-0"
        mip: day
      tasmin:
        preprocessor: preproc
        reference_dataset: "ACCESS1-0"
        mip: day

    scripts:
      extreme_events:
        script: extreme_events/extreme_events.R
        reference_datasets: ["ACCESS1-0", "ACCESS1-0", "ACCESS1-0"]
        regrid_dataset: ACCESS1-0
        mip_name: CMIP
        timeseries_idx: ["tn10pETCCDI_yr", "tn90pETCCDI_yr", "tx10pETCCDI_yr", "tx90pETCCDI_yr"]
        gleckler_idx: ["tn10pETCCDI_yr", "tn90pETCCDI_yr", "tx10pETCCDI_yr", "tx90pETCCDI_yr"]
        ts_plt: false
        glc_plt: false
        base_range: [1980, 1983]
        analysis_range: [1980, 1985]

      hyint:
        script: hyint/hyint.R
        ancestors: [pr, extreme_events]
 
        # Reference normalization period to be used for normalized indices
        norm_years: [1980, 1983]

        # Call preprocessing for ETCCDI indices calculated with climdex
        etccdi_preproc: true

        # Specify external path to repository of ETCCDI indices 
        # (unless these are calculated in the same directory)
        #etccdi_dir: "./work/hyint/main"

        # Select indices to be imported from the extreme_events metrics:
        etccdi_list_import: ["tn10pETCCDI", "tn90pETCCDI", "tx10pETCCDI", "tx90pETCCDI"] 

        # Select one or more indices for timeseries and maps from the following
        # list (order-sensitive):
        # "pa_norm", "hyint",  "int_norm", "r95_norm", "wsl_norm", "dsl_norm", "int", "dsl", "wsl"
        # "altcddETCCDI", "altcsdiETCCDI", "altcwdETCCDI",
        # "altwsdiETCCDI", "cddETCCDI", "csdiETCCDI", "cwdETCCDI",
        # "dtrETCCDI", "fdETCCDI", "gslETCCDI", "idETCCDI",
        # "prcptotETCCDI", "r10mmETCCDI", "r1mmETCCDI", "r20mmETCCDI",
        # "r95pETCCDI", "r99pETCCDI", "rx1dayETCCDI", "rx5dayETCCDI",
        # "sdiiETCCDI", "suETCCDI", "tn10pETCCDI", "tn90pETCCDI",
        # "tnnETCCDI", "tnxETCCDI", "trETCCDI", "tx10pETCCDI",
        # "tx90pETCCDI", "txnETCCDI", "txxETCCDI", "wsdiETCCDI"
        select_indices: ["pa_norm", "hyint", "tn10pETCCDI", "tn90pETCCDI", "tx10pETCCDI", "tx90pETCCDI"]

        # Select regions for timeseries and maps from the following list
        # GL=Globe, GL60=Globe 60S/60N, TR=Tropics (30S/30N), SA=South America,
        # AF =Africa,6NA=North America, IN=India, EU=Europe, EA=East-Asia,
        # AU=Australia
        select_regions: ["GL", "GL60", "TR"]

        # Select type of plot:
        # 1) single panel lon/lat map per individual index, multi-year mean
        # 2) 3-panel lon/lat maps per individual index with comparison to reference dataset, multi-year mean
        # 3) multipanel of indices of lon/lat maps with comparison to reference dataset, multi-year mean
        # 11) single panel with timeseries over required individual region
        # 12) multipanel of indices with timeseries over multiple regions
        # 13) multipanel of indices with timeseries for multiple models
        # 14) multipanel of indices with summary of trend coefficients over multiple regions
        # 15) multipanel of indices with summary of trend coefficients for multiple models
        plot_type: [3, 12, 13, 15]

        ## ------- Optional settings ----------
        # Select number of columns and rows in multi-panel figure
        npancol: 2  # number of columns for trend/tseries multi-panel figures
        npanrow: 3  # number of rows for trend/tseries multi-panel figures

        # Define whether model data should be regridded
        # a) false to keep original resolution
        # b) set desired regridding resolution in cdo format e.g., "r320x160"
        # c) "REF" to use resolution of reference model
        rgrid: REF

        # Select automated or pre-set range of values in plots
        autolevels: true

        # Scale autolevels (factor multiplying automated range)
        autolevels_scale: 1  # for maps and timeseries
        autolevels_scale_t: 1  # for trend coefficients

        # data and maps
        removedesert: false  # T to remove (flag as NA) grid points with mean
                             # annual pr < 0.5 mm/day (deserts, Giorgi2014)
        oplot_grid: false  # plot grid points over maps
        boxregion: false  # !=0 plot region boxes over global maps with
                          # thickness = abs(boxregion); white (>0) or grey (<0).

        # timeseries and trends
        weight_tseries: true  # adopt area weights in timeseries
        trend_years: false    # (a) F=all; (b) c(year1,year2) to apply trend
                              # calculation and plotting only to a limited
                              # time interval
        add_trend: true             # add linear trend to plot
        add_trend_sd: true          # add stdev range to timeseries
        add_trend_sd_shade: true    # add shade of stdev range to timeseries
        add_tseries_lines: true     # lot lines of timeseries over points
        add_zeroline: true          # plot a dashed line at y=0
        trend_years_only: false     # limit timeseries plotting to trend_years
                                    # time interval
        scale100years: true         # plot trends as 1/100 years
        scalepercent: false         # plot trends as % change (excluding hyint)